Segmentation of multigradation images based on spatial connectivity features

• Autorzy: Timchenko Leonid , Kokriatskaia Natalia , Tverdomed Volodymyr , Stetsenko Oleksandr , Kaplun Valentyna , Kolesnytskyj Oleh , Reshetnik Oleksandr , Smailova Saule , Zhunissova Ulzhalgas

Identyfikatory

DOI

10.35784/iapgos.5352

Warianty tytułu

PL

Segmentacja obrazów wielogradacyjnych na podstawie cech łączności przestrzennej

• Języki publikacji: EN

Abstrakty

EN

The article aims to study the multi-level segmentation process of images of arbitrary configuration and placement based on features of spatial connectivity. Existing image processing algorithms are analyzed, and their advantages and disadvantages are determined. A method of organizing the process of segmentation of multi-gradation halftone images is developed and an algorithm of actions according to the described method is given.

PL

Artykuł ma na celu zbadanie procesu wielopoziomowego segmentacji obrazów o dowolnej konfiguracji i rozmieszczeniu w oparciu o cechy łączności przestrzennej. Przeanalizowano istniejące algorytmy przetwarzania obrazu oraz określono ich zalety i wady. Opracowano metodę organizacji procesu segmentacji wielogradacyjnych obrazów półtonowych i przedstawiono algorytm działań zgodnie z opisaną metodą.

Słowa kluczowe

EN

image segmentation; image processing; halftone image; spatial connectivity

PL

segmentacja obrazu; przetwarzanie obrazu; obraz półtonowy; łączność przestrzenna

• Wydawca: Wydawnictwo Politechniki Lubelskiej
• Czasopismo: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
• Rocznik: 2023
• Tom: T. 13, nr 3
• Strony: 47--50
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Timchenko Leonid

• State University of Infrastructureand Technology, Artificial Intelligence Systems and Telecommunication Technologies Department, Kyiv, Ukraine

• https://orcid.org/0000-0001-5056-5913

autor

Kokriatskaia Natalia

• State University of Infrastructureand Technology, Artificial Intelligence Systems and Telecommunication Technologies Department, Kyiv, Ukraine

• https://orcid.org/0000-0003-0090-3886

autor

Tverdomed Volodymyr

• State University of Infrastructureand Technology, Artificial Intelligence Systems and Telecommunication Technologies Department, Kyiv, Ukraine
• Kyiv Institute of Railway Transport, Kyiv, Ukraine

• https://orcid.org/0000-0002-0695-1304

autor

Stetsenko Oleksandr

• State University of Infrastructureand Technology, Artificial Intelligence Systems and Telecommunication Technologies Department, Kyiv, Ukraine

• https://orcid.org/0000-0001-8359-0218

autor

Kaplun Valentyna

• Vinnytsia National Technical University, Vinnytsia, Ukraine

• https://orcid.org/0000-0003-4353-3694

autor

Kolesnytskyj Oleh

• Vinnytsia National Technical University, Vinnytsia, Ukraine

• https://orcid.org/0000-0003-0336-4910

autor

Reshetnik Oleksandr

• Vinnytsia National Technical University, Vinnytsia, Ukraine

• https://orcid.org/0009-0006-7320-329X

autor

Smailova Saule

• D.Serikbayev East Kazakhstan State Technical University,Ust-Kamenogorsk, Kazakhstan

• https://orcid.org/0000-0002-8411-3584

autor

Zhunissova Ulzhalgas

• Astana Medical University, Astana, Kazakhstan

• https://orcid.org/0000-0001-5255-9314

Bibliografia

• [1] Avrunin O. G. et al.: Features of image segmentation of the upper respiratory tract for planning of rhinosurgical surgery. 2019 IEEE 39th International Conference on Electronics and Nanotechnology, ELNANO 2019, 485–488.
• [2] Avrunin O. G. et al.: Research Active Posterior Rhinomanometry Tomography Method for Nasal Breathing Determining Violations. Sensors 21, 2021, 8508 [http://doi.org/10.3390/s21248508].
• [3] Bradski G., Kaehler A.: Learning Open CV, second edition. 2013.
• [4] Burgener F. et al.: Differential Diagnosis in Computed Tomography, 2011.
• [5] Campbell J.: Human Medical Thermography, 2022.
• [6] Comaniciu D., Meer P.: Mean shift analysis and applications. IEEE International Conference on Computer Vision 2, 1999, 1197.
• [7] Comaniciu D., Meer P.: Mean Shift: A Robust Approach Toward Feature Space Analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002, 603–619.
• [8] Comaniciu D., Ramesh V., Meer P.: Real-Time Tracking of Non-Rigid Objects Using Mean Shift. Conference on CVPR 2, 2000, 1–8.
• [9] Gonzalez R., Woods R: Digital Image Processing. Technosphere, 2012.
• [10] Haralik R. M.: Statistical and structural approaches to the description of textures. Proceedings of the Institute of Electronics and Radio Engineering, 1979, 98–120.
• [11] Kurmi Y., Chaurasia V.: Multifeature-based medical image segmentation. Sensors, 2018.
• [12] Linda G. S. Stockman G. C.: Computer Vision, 2001.
• [13] Orazayeva A. et al.: Biomedical image segmentation method based on contour preparation. Proc. SPIE 12476, 2022, 1247605 [http://doi.org/10.1117/12.2657929].
• [14] Rodriguez-Lozano F. J., León-García F., Ruiz de Adana M., Palomares J. M., Olivares J.: Non-Invasive Forehead Segmentation in Thermographic Imaging. Sensors 19, 2019, 4096 [http://doi.org/10.3390/s19194096].
• [15] Romanyuk O. N.: A function-based approach to real-time visualization using graphics processing units. Proc. SPIE 11581, 2020, 115810E [http://doi.org/10.1117/12.2580212].
• [16] Rother С., Kolmogorov V., Blake Grabcut A.: Interactive foreground extraction using iterated graph cuts, 2004.
• [17] Timchenko L. I. et al.: Q-processors for real-time image processing. Proc. SPIE 11581, 2020, 115810F [http://doi.org/10.1117/12.2580230].
• [18] Timchenko L. I., Kutaev Y. F.: Method and organization of image extraction. Patent 2024939С1 RF, MKI G 06 K 9/00, 1992-07-08, 1992.
• [19] Vapnik V.N., Chervonenkis A.Y.: Pattern recognition theory (statistical learning problems). Science, 1974.
• [20] Wójcik W., Smolarz A.: Information Technology in Medical Diagnostics (1st ed.). CRC Press 2017 [http://doi.org/10.1201/9781315098050].

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).